Imposing physical constraints (previous knowledge) in a neural network for regression
Some ideas out the top of my head:


In the case of $dy/dx_2&gt;0$ you could compute the gradient using the chain rule and limit the weights so that the constrain holds
In the case of $y + x_5 + x_7 &lt; K$ you could use a clipping function on the output layer?